基于饮食模式的大学生肥胖的风险因素分析和预测模型
Jiawang Bai1,2, Mengyuan Chen1,2, Wenfeng Hou1,2
1School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Frontiers in nutrition
|September 29, 2025
概括
大学生面临高肥胖风险. 一种使用体脂百分比的新型诺莫格拉姆模型有效预测肥胖,识别饮食和生活方式因素. 需要进一步验证.
科学领域:
- 公共卫生 公共卫生
- 营养科学 营养科学
- 生物统计学 生物统计学
背景情况:
- 超重和肥胖是大学生中关键的公共卫生问题.
- 患病率需要有效的风险评估工具来进行早期干预.
研究的目的:
- 开发一种名图模型,用于评估大学生肥胖风险.
- 根据身体脂肪百分比来确定肥胖的关键预测因素.
主要方法:
- 涉及徐州大学生的横截面研究.
- 通过问卷和InBody 570身体成分分析收集数据.
- 主要组件分析 (PCA),物流回归和名ogram模型的应用.
主要成果:
- 特定的饮食模式 (蔬菜-谷物,牛奶-蛋) 与减少体脂百分比 (PBF) 相关,而其他 (零食,水生肉) 增加了PBF.
- 确定了关键预测因素:性别,体力活动,深夜小吃,饮食规律和饮食质量.
- 开发的诺莫格拉姆模型显示出良好的预测性能 (AUC=0.805) 和可靠性 (非显著的HL测试,有利的DCA).
结论:
- 这项研究证实了高肥胖率和大学生全面评估的必要性.
- 一种基于PBF的新型诺莫格拉姆模型显示出对这一群体的肥胖查有前途.
- 为了更广泛的适用性,建议在多样化的学生群体中进一步验证.
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